As Robohub puts it, the work done by the ETH Zurich masters thesis student Dario Brescianini, who works in the Flying Machine Arena, tacked “two of the most challenging problems [...] with quadrocopters.” That is, balancing an inverted pendulum and juggling balls.

Here’s what Brescianini wrote about the project, according to Robohub:

This project was very interesting because it combined various areas of current research and many complex questions had to be answered: How can the pole be launched off the quadrocopter? Where should it be caught and – more importantly – when? What happens at impact?

The biggest challenge to get the system running was the catching part. We tried various catching maneuvers, but none of them worked until we introduced a learning algorithm, which adapts parameters of the catching trajectory to eliminate systematic errors.

Brescianini and his advisers used a state estimator to predict the pendulum’s motion while it was airborne and when it was caught by the other quadrocopter. This feature, Robohub explained, allowed the quadrocopter to be in the correct position to catch the pendulum and then switch to balancing it once it landed.

A fast trajectory generator was used to make sure the drone moved fast enough to get into catching position.

One of the problems encountered while testing methods to balance, throw and catch the pendulum, included that mistakes were expensive. Robohub stated that if the quadrocopter missed catching the pendulum, it often hit one of the blades, setting the device on a crash course that often resulted in damage and required recalibration.